PERENCANAAN PENGIRIMAN DAN KAPASITASPENYIMPANAN TERINTEGRASI: SEBUAH STUDI SIMULASI

In a transportation and distribution system, the shipment decisions, fleet capacity, and storage capacity are interrelated in a complex way, especially when uncertainty of the demand rate and shipment lead time are taken into account. In this paper the effect of various factors on total costs and service level of a distribution system are investigated. The objective is to obtain a better policy related to a number of issues in transportation and distribution under uncertain situation and to obtain insights on which factor affect the performance significantly. This research develops a simulation model that mimics transportation and distribution of bulk cement by the use of ships in a large cement company in Indonesia. The system consists of a storage at the depot and storage at two port of destinations, which then referred to as packing plants. Several numbers of scenario related to storage capacity at port of origins as well as port of destinations, number of ships employed, operating hours of ports, and rules for ship dispatching are then developed. Each scenario is evaluated in terms of shipment costs and service level. A factorial experiment has been conducted and ANOVA has been used to analyze the results. The results suggest that all factors have significant effects on both total costs and service level. However, the use of different number of ships appear to have the most substantial impacts on those two performance measures. It is also observed that a strong correlation exists between total costs and service level and an efficient frontier of cost and service level has been presented. This paper brings an important recommendation to the company as well as insight for maritime logistics in general. Cost is a very important competitive factor for bulk items like cement, and thus the proposed scenarios could be implemented by the company for substantial transportation and distribution cost reduction. In addition, the efficient frontier graph resulted from this study can be used as an internal target or performance benchmark.